Python

The python code for the pre-trained transformer model approach can be found in Python/entity-resolution-clust.ipybn. The code that investigates comparisons between string transformations can be found in Python/PROSE-transformations.ipynb. We chose to use jupyter notebooks to clearly lay out our experiments in a step-by-step manner. To run the notebooks, first create the conda environmnet with all necessary packages by running conda env create -f environment.yml from the Python directory. Then you can run the jupyter notebooks using the ent-res-cons environment.